Urban Outfitters Cuts Fraud Order Reviews With Machine Learning

When Urban Outfitters, Inc. deployed Accertify® Fraud Management in 2009, the international retailer already had a large staff of fraud analyts. The formula was "high order review rate to stop fraud," according to Bryan Whitney, Director Contact Center over direct channel fraud control at Urban Outfitters, Inc. The need was acute as eCommerce was rapidly growing and with the growth attempted fraud grew with it. Reacting to need, the company deployed Accertify's solution to automate fraud management processes and get better results identifying fraud. Since then, Urban Outfitters, Inc. has continued accruing benefits from Accertify Fraud Management, and subsequently deployed Chargeback Management and Profile Builder.

Looking for new ways to continuously improve upon reduced order review rates, Urban Outfitters, Inc. came to Accertify in 2015, asking about moving to the next step of machine learning based on statistical models.

Solution

Standard fraud detection relies on rules for evaluating transaction variables. A machine learning technique such as Gradient Boosting Machine (GBM) can analyze and lever a significantly higher number of variables and improve predictive power. The analytical results enable more identification of risk and require less human intervention. Urban Outfitters, Inc. deployed Accertify's machine learning GBM model in late 2015 and cut fraud order reviews 20%.